Triple
T6634690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the National Order of Merit (France) |
E150417
|
entity |
| Predicate | orderOfPrecedenceInFrance |
P1803
|
FINISHED |
| Object | below the Legion of Honour |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: below the Legion of Honour | Statement: [Officer of the National Order of Merit (France), orderOfPrecedenceInFrance, below the Legion of Honour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderOfPrecedenceInFrance Context triple: [Officer of the National Order of Merit (France), orderOfPrecedenceInFrance, below the Legion of Honour]
-
A.
economicRankInFrance
Indicates the relative economic standing or ranking of an entity within the context of France’s economy.
-
B.
orderPrecedence
chosen
Indicates that one entity must come before another in a defined sequence or priority order.
-
C.
orderPrecedenceInCanada
Indicates the relative legal or procedural priority that one item holds over another specifically within the Canadian context.
-
D.
orderPrecedenceInSweden
Indicates the hierarchical ranking or protocol precedence between entities within the Swedish order of precedence system.
-
E.
populationRankInFrance
Indicates the relative position of an entity in an ordered list based on its population size within France.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.